Automatic radiotherapy plan emulation for 3D dose reconstruction to enable big data analysis for historically treated patients

摘要

3D dose reconstruction for radiotherapy (RT) is the estimation of the 3D radiation dose distribution patients receivedduring RT. Big dose reconstruction data is needed to accurately model the relationship between the dose and onset ofadverse effects, to ultimately gain insights and improve today’s treatments. Dose reconstruction is often performed byemulating the original RT plan on a surrogate anatomy for dose estimation. This is especially essential for historicallytreated patients with long-term follow-up, as solely 2D radiographs were used for RT planning, and no 3D imaging wasacquired for these patients. Performing dose reconstruction for a large group of patients requires a large amount ofmanual work, where the geometry of the original RT plan is emulated on the surrogate anatomy, by visually comparingthe latter with the original 2D radiograph of the patient. This is a labor-intensive process that for practical use needs to beautomated. This work presents an image-processing pipeline to automatically emulate plans on surrogate computationaltomography (CT) scans. The pipeline was designed for childhood cancer survivors that historically received abdominalRT with anterior-to-posterior and posterior-to-anterior RT field set-up. First, anatomical landmarks are automaticallyidentified on 2D radiographs. Next, these landmarks are used to derive parameters needed to finally emulate the plan ona surrogate CT. Validation was performed by an experienced RT planner, visually assessing 12 cases of automatic planemulations. Automatic emulations were approved 11 out of 12 times. This work paves the way to effortless scaling ofdose reconstruction data generation.